RESEARCH ARTICLE
Nitrogen Fertilization Effects on Productivity
and Nitrogen Loss in Three Grass-Based
Perennial Bioenergy Cropping Systems
Brianna E. L. Duran1,2, David S. Duncan1,2, Lawrence G. Oates1,2*, Christopher
J. Kucharik1,2, Randall D. Jackson1,2
1 Department of Agronomy, University of Wisconsin, Madison, United States of America, 2 DOE—Great
Lakes Bioenergy Research Center, University of Wisconsin, Madison, United States of America
* oates@wisc.edu
Abstract
OPEN ACCESS
Citation: Duran BEL, Duncan DS, Oates LG,
Kucharik CJ, Jackson RD (2016) Nitrogen
Fertilization Effects on Productivity and Nitrogen Loss
in Three Grass-Based Perennial Bioenergy Cropping
Systems. PLoS ONE 11(3): e0151919. doi:10.1371/
journal.pone.0151919
Editor: R. Michael Lehman, USDA-ARS, UNITED
STATES
Received: November 25, 2015
Accepted: March 7, 2016
Published: March 18, 2016
Copyright: © 2016 Duran et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
Data Availability Statement: All data have been
submitted to Dryad, with the following DOI: http://dx.
doi.org/10.5061/dryad.m717n
Funding: This work was funded in part by the DOE
Great Lakes Bioenergy Research Center (https://
www.glbrc.org/)(DOE BER Office of Science DEFC02-07ER64494; http://science.energy.gov/) and
DOE OBP Office of Energy Efficiency and Renewable
Energy (DE-AC05-76RL01830; http://energy.gov/
eere/office-energy-efficiency-renewable-energy), the
Water Sustainability and Climate Program of the
National Science Foundation (DEB-1038759), a
Nitrogen (N) fertilization can greatly improve plant productivity but needs to be carefully
managed to avoid harmful environmental impacts. Nutrient management guidelines aimed
at reducing harmful forms of N loss such as nitrous oxide (N2O) emissions and nitrate
(NO3-) leaching have been tailored for many cropping systems. The developing bioenergy
industry is likely to make use of novel cropping systems, such as polycultures of perennial
species, for which we have limited nutrient management experience. We studied how a
switchgrass (Panicum virgatum) monoculture, a 5-species native grass mixture and an 18species restored prairie responded to annual fertilizer applications of 56 kg N ha-1 in a fieldscale agronomic trial in south-central Wisconsin over a 2-year period. We observed greater
fertilizer-induced N2O emissions and sub-rooting zone NO3- concentrations in the switchgrass monoculture than in either polyculture. Fertilization increased aboveground net primary productivity in the polycultures, but not in the switchgrass monoculture. Switchgrass
was generally more productive, while the two polycultures did not differ from each other in
productivity or N loss. Our results highlight differences between polycultures and a switchgrass monoculture in responding to N fertilization.
Introduction
Nitrogen (N) pollution from agricultural systems has local, regional, and global environmental
impacts. Nitrate (NO3-) leaching can negatively impact drinking water quality [1] and contributes to eutrophication events such as the Gulf of Mexico hypoxic zone [2,3]. Ammonia volatilization contributes to acid precipitation, while nitrous oxide (N2O) is the single greatest
ongoing source of ozone depletion [4] and an extremely potent greenhouse gas [5]. These
forms of N pollution are commonly linked to excessive or misapplied N fertilizer [6,7]. To
combat this, nutrient application guidelines and best management practices have been developed for many major cropping systems (e.g. [8]). These guidelines rely on knowledge about a
cropping system and its performance under diverse conditions; however, such knowledge may
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
Multi-State Hatch Grant (#WISO1420), the UW
Department of Agronomy, and the D.C. Smith
Wisconsin Distinguished Graduate Fellowship. The
funders had no role in study design, data collection
and analysis, decision to publish, or preparation of
the manuscript.
Competing Interests: The authors have declared
that no competing interests exist.
be lacking for novel cropping systems such as perennial polycultures. Generating data on N
dynamics and idiosyncrasies is thus a key element in the development of a novel cropping
system.
The ongoing development of cellulosic (i.e. “second generation”) biofuels has spurred interest in the use of diverse mixtures of perennial species as biomass feedstock cropping systems
[9]. Second generation biofuels use cellulose and other non-edible plant materials, in contrast
to first generation fuels, which are produced from edible sugars, starches, or oils [10]. This creates the possibility of commercializing land covers, such as diverse assemblages of tallgrass
prairie species, which have previously been valued purely for their aesthetic and ecological
properties [11]. Despite their benefits, these systems lack the wealth of agronomic knowledge
available for more conventional crops [12]. A growing body of research and experience informs
management of certain biomass feedstock species, most notably switchgrass (Panicum virgatum) [13,14], but knowledge of the agronomic behaviors of polycultures in bioenergy feedstock
cropping systems is much less developed [15]. As fertilization will likely be necessary for sustaining high levels of productivity in these systems [16], it will be critical to understand the
agronomic and ecological dynamics of polyculture cropping systems.
A sizeable body of ecological research and theory explores the role of plant community
diversity and composition in ecosystem functioning. Many studies find increasing the number
of species present correlates to greater plant productivity [17,18], although multispecies assemblages rarely out-produce monocultures of highly productive species [19]. In some cases,
increasing the number of species and functional groups in a plant community decreases soil
N2O emissions [20,21] and reduces soil NO3- pools [22,23]. The effect of species diversity on
ecosystem dynamics is frequently attributed to complementarity, where differences in speciesspecific resource utilization result in more complete exploitation of ecosystem resources
[24,25]. Nutrient management strategies designed for particular species in monoculture may
thus yield different results in diverse species assemblages.
In this study, we explore how nitrogen fertilization impacts N loss pathways and plant productivity in three biomass production systems based on grasses and forbs native to North
America. The systems we studied were a switchgrass monoculture, a mixture of five grasses,
and a mixture of 18 prairie species. All systems were managed at agronomic scale and split into
plots receiving either replacement-level N fertilizer or no fertilizer. For each system, we measured aboveground productivity, N2O emissions, and potential NO3- leaching, with the aim of
determining how these properties were impacted by N fertilization in the three systems.
Materials and Methods
Field sites
The study was conducted at the Great Lakes Bioenergy Research Center’s Biofuel Cropping
Systems Experiment (BCSE) at the Arlington Agricultural Research Station (Arlington, WI,
43°17’45” N, 89°22’48” W, 315 masl) during the 2011 and 2012 field seasons. Predominant
soils are classified as Plano silt loam (Fine-silty, mixed, superactive, mesic Typic Argiudoll).
Mean annual air temperature and precipitation are 6.8°C and 869 mm respectively [26].
Cumulative precipitation and average daily temperature for 2011 and 2012 are given in the
supporting information (S1 Fig).
The BCSE was established in 2008 and contains eight cellulosic biofuel feedstock production
systems managed at agronomic scale in a randomized complete block design with five replicates (five blocks). We selected three blocks where other studies were conducting more intensive biophysical parameter modeling from which to sample. From the eight cropping systems,
we selected three systems that formed a spectrum of species diversity: monoculture switchgrass
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
(var. ‘Cave-in-Rock’), a mixture of five grasses native to the region (“native grasses”), and a
mixture of 18 grass and forb species native to the region (“restored prairie”, see Table 1 for
composition and diversity details). Switchgrass and mixed grass plots received early-season
weed management through 2011; switchgrass received weed management again in 2012. The
restored prairie received weed control in its establishment year, but none in subsequent years.
Plots were 27 m wide × 43 m long (0.12 ha), with a 17 m wide main plot and two 5 m wide
subplots (S2 Fig). The switchgrass and mixed grass main plots as well as the restored prairie
subplot received annual applications of 56 kg ha-1 N as ammonium nitrate. Fertilizer was
applied with a vacuum spreader when C4 grasses were 30–45 cm tall (2011-05-27 and 201205-11) in keeping with University of Wisconsin recommendations for management of established switchgrass stands [8]. The restored prairie main plot and the subplots of switchgrass
and native grasses received no fertilization after establishment. The BCSE was established in
spring 2008 and all systems have been harvested to a residual stubble height of 10 cm annually
since 2009. We sampled at three randomly positioned 1.5 × 1.5 m quadrats (subsamples)
within both main and subplots. Quadrats remained in place during the growing season, but
were repositioned in the subsequent year (S2 Fig).
Table 1. Seeded species and measures of realized diversity and composition in three biofuel feedstock production systems.
Switchgrass
Native grasses
Restored prairie
Species richness
3.6 ± 1.9
6.0 ± 2.0
10.9 ± 1.7
Shannon’s diversity index
0.7 ± 0.4
1.4 ± 0.3
1.9 ± 0.2
C3 grass cover (%)
5.0 ± 11.0
72.7 ± 29.8
90.2 ± 22.7
C4 grass cover (%)
127.2 ± 49.2
103.2 ± 47.5
21.1 ± 22.5
Non-legume forb cover (%)
11.9 ± 18.8
6.8 ± 11.3
86.5 ± 24.9
Legume cover (%)
none observed
none observed
10.4 ± 14.2
Seeded species
Panicum virgatum L.
Panicum virgatum L.
Panicum virgatum L.
Andropogon gerardii Vitman
Andropogon gerardii Vitman
Elymus canadensis L.
Elymus canadensis L.
Schizachyrium scoparium (Michx.) Nash
Schizachyrium scoparium (Michx.) Nash
Sorghastrum nutans L.
Sorghastrum nutans L.
Koeleria macrantha (Ledeb.) Schult.
Anemone canadensis L.
Asclepias tuberosa L.
Baptisia alba (L.) Vent. var. macrophylla (Larisey) Isley
Desmodium canadense (L.) DC.
Lespedeza capitata Michx.
Monarda fistulosa L.
Oligoneuron rigidum (L.) Small var. rigidum
Ratibida pinnata (Vent.) Barnhart
Rudbeckia hirta L.
Silphium perfoliatum L.
Solidago erecta Pursh
Symphyotrichum novae-angliae (L.) G.L.Nesom.
Cover measurements allowed multiple species hits per point; functional group cover is summed over all species and can thus exceed 100%. Values are
means ± standard deviation.
doi:10.1371/journal.pone.0151919.t001
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
Nitrous oxide emissions
Soil N2O fluxes were measured twice monthly from 9 May to 14 September 2011 and 7 May to
6 September 2012. N2O measurement and flux estimation largely followed the approach of
Oates et al. [27]. Briefly, 27.15 cm diameter stainless steel non-through flow chambers were
inserted 5.5 cm into the soil to an effective height of 17.3 cm for a headspace volume of 10 l.
Chambers were placed in the center of marked quadrats. Plants growing within the chambers
were clipped flush with the chamber top at least 24 h before measurement to allow lid closure
[28]. Gas was measured by sealing the chamber and sampling headspace gas at 10 minute intervals for 30 minutes. Gas concentrations were measured by gas chromatography with a 15 mCi
63
Ni electron capture detector for N2O (Agilent 7890A GC system) and infra-red gas analyzer
for CO2 (LI-COR LI-820 CO2 analyzer).
N2O fluxes were estimated through the HMR method [29], implemented in the R package
'HMR' (v0.3.1, [30]). We previously found the HMR method to be more appropriate than linear regression at long chamber deployment times [31]. Package recommendations were followed, with secondary visual inspection for samples where linear and nonlinear fluxes differed
by 0.01 mg N2O-N m-2 h-1. Linear interpolation between measurement dates was used to
estimate cumulative N2O emission over the growing season. Emissions factor (EF), the percentage of fertilizer N released as N2O, was calculated as:
EF ¼
N2 OF
N2 OU
FN
%
where N2OF and N2OU are cumulative N2O emissions (kg N ha-1) for adjacent fertilized and
unfertilized subplots respectively and FN is the nitrogen content (kg N ha-1) of fertilizer applied
[32,33].
Soil inorganic nitrogen
We sampled extractable soil NO3- at the 50–80 cm depth. This was interpreted as potentially
leachable NO3-, as root biomass and plant nutrient uptake are concentrated in the top 50 cm of
soil [34,35]. We sampled periodically throughout the growing season in both years (S3 Fig),
but focused our analysis on samples taken near peak plant biomass. The N content of C4
grasses reaches a maximum concurrent with peak biomass [36], so our samples should represent N that escaped below the rooting zone during the period of greatest plant N utilization.
Three soil samples were removed from each quadrat and composited. Samples were homogenized and sieved to 2 mm, with rocks and biomass removed. Within 48 h of field sampling, 10
g soil samples were extracted with 2 M KCl [37]. Extracts were frozen prior to colorimetric
NO3- determination (according to USEPA Method 353.2, O-I-Analytical Method #2648) using
a Flow Solution 3100 segmented flow injection analyzer (OI Analytical, College Station, TX).
Soil subsamples (15 g) were weighed, oven-dried for 48 h at 60°C, and then reweighed to obtain
soil gravimetric water content.
Ancillary environmental measurements
Soil temperature and moisture were measured concurrently with trace gas sampling to identify
potential abiotic drivers of flux differences among systems [38,39]. Soil temperature measurements were taken with a 10 cm probe (Checktemp 1C, Hanna Instruments, Smithfield, RI); soil
volumetric water content was measured using a 6 cm ML3 ThetaProbe sensor (Dynamax,
Houston, TX). In both cases, we took 3 measurements within 25 cm of the sampling chamber
and averaged them. Volumetric water content was converted to water-filled pore space
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
(WFPS) using bulk densities measured at the plot level in 2008 and a standard soil particle density of 2.65 g cm-3. WFPS is commonly linked to microbial nitrification and denitrification
[40].
Aboveground productivity and biomass properties
After all field measurements were completed (23 to 30 September 2011 and 21 to 27 August
2012), all aboveground biomass from each quadrat was hand-harvested to ground level and
then dried and weighed to estimate aboveground net primary productivity (ANPP). ANPP
peaked earlier in 2012 due to above-average March temperatures and an early summer drought
(S1 Fig). Plant species cover was measured immediately prior to harvest using the point-intercept method [41]. Each quadrat was divided into 49 evenly-spaced points at which each unique
plant species intercepted by a dropped rod was recorded. The percent cover for each species
was estimated as the percentage of points at which the species was observed. Multiple species
could be counted at each point, so percent cover summed over all species could exceed 100%
[41]. In addition to quadrat-level data, entire plots (main and subplot) were harvested to 10 cm
stubble height following a killing frost (10 October 2011 and 7 November 2012). Total N content of a representative subsample of the harvested material was determined by combustion
using a Flash EA 1112 Automated Elemental Analyzer (Thermo Finnigan, Milan, Italy).
Statistical analysis
Data analysis was conducted in the R statistical environment (v3.1.1, [42]). Values for N2O
emissions and NO3- concentrations were log-transformed prior to analysis to meet assumptions of normality. Negative NO3- concentrations were replaced with half the smallest positive
concentration observed (0.04 μg N g-1 dry weight soil). All analyses used linear mixed effect
models from the R package 'nlme' (v3.1.1, [43]). We employed a nested random effects structure of subsample within subplot within plot within block (S2 Fig) to properly account for lack
of independence in our data. We allowed variances to differ among treatments, identifying the
most parsimonious grouping structure by likelihood ratio comparison of nested models. Significance of treatment differences was done separately by year using the R package 'lsmeans'
(v1.06, [44]) and a Tukey-corrected P < 0.05 cutoff.
Results
Fertilization increased nitrous oxide emissions more in switchgrass than
in polycultures
Crop type and fertilizer effects on total N2O emissions were significant in both years (Fig 1A
and 1B). Fertilization increased emissions in all cases except for native grasses in 2012, where it
had no effect. With equal fertilization, N2O emissions were comparable between the polycultures and lower than switchgrass. In 2011, N2O emissions from all crop types were approximately 3 times greater from the fertilized plots when compared to the unfertilized plots (Fig
1A). Emission factors in 2011 were 2.4% (s.e. ± 0.65%), 0.26% (s.e. ± 0.13%), and 0.56% (s.e. ±
0.26%) for switchgrass, native grasses, and restored prairie, respectively. In 2012, nitrogen fertilization similarly tripled N2O emissions from switchgrass, but did not impact the polycultures
(Fig 1B). Emission factors for 2012 were 1.5% (s.e. ± 0.48%), 0.018% (s.e. ± 0.041%), and 0.23%
(s.e. ± 0.025%) for switchgrass, native grasses, and restored prairie, respectively.
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
Fig 1. Average N losses and aboveground net primary productivity (ANPP) for each crop and fertilizer treatment in 2011 and 2012. Within each
panel, samples sharing a letter are not significantly different (P > 0.05), n.s. indicates no significant differences among samples. (a) Average total N2O
emissions for the measurement period (May-September) are given as back-transformed geometric means ± standard error. (b) Average sub-rooting zone
NO3- concentrations are given as back-transformed geometric means ± standard error. (c) Average aboveground productivity values are given as arithmetic
means ± standard error.
doi:10.1371/journal.pone.0151919.g001
Potential nitrate leaching increased with fertilization in switchgrass
In both years, fertilized switchgrass had higher NO3- concentrations below the rooting zone
than the polycultures, while all other cropping system × fertilization combinations were comparable (Fig 1C and 1D). Across all systems, NO3- concentrations were lower in 2012 than
2011. In 2011, there was no significant effect of fertilizer on potential leaching (Fig 1C). In
2012 there was a crop × fertilizer effect with higher potential leaching in fertilized versus unfertilized switchgrass, but no fertilizer effect in the polycultures (Fig 1D). Regardless of fertilizer
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
Table 2. Relationship between nitrogen loss and aboveground net primary productivity (ANPP) production in three bioenergy cropping systems.
g N loss Mg-1 biomass
NO3-
N2O
Year
Crop
Fertilizer treatment
2011
Switchgrass
Fertilized
Unfertilized
39
(31–48)
ab
312
(179–541)
a
Native grasses
Fertilized
20
(17–25)
b
277
(162–472)
a
Unfertilized
10
(7–13)
b
321
(185–559)
a
Restored prairie
Fertilized
34
(26–43)
ab
253
(153–421)
a
Unfertilized
12
(9–15)
b
391
(225–680)
a
Switchgrass
Fertilized
125
(95–164)
a
483
(344–677)
a
Unfertilized
29
(23–36)
b
71
(47–106)
b
Fertilized
18
(15–22)
b
81
(51–129)
ab
Unfertilized
26
(20–32)
b
130
(84–200)
ab
Fertilized
31
(26–38)
b
49
(33–73)
b
Unfertilized
31
(16–27)
b
99
(61–161)
ab
2012
Native grasses
Restored prairie
114
(94–139)
a
513
(295–892)
a
Values are geometric means, with ± 1 s.e. in parentheses. Within a year and column, values sharing a letter are not significantly different (P > 0.05).
doi:10.1371/journal.pone.0151919.t002
use, early season soil NO3- was higher in switchgrass than either polyculture, while later-season
values converged among crops (S3 Fig). The exception was the unfertilized crops in 2012
where NO3- values differed among all three systems in the early season but converged by peak
biomass.
Aboveground net primary productivity of polycultures increased by
fertilization
Fertilization increased ANPP in polycultures, although the increase was only significant for
restored prairie in 2011 and native grasses in 2012 (Fig 1E and 1F). In contrast, fertilization did
not significantly increase switchgrass ANPP in 2011 and reduced it in 2012. Switchgrass was
generally more productive than the polycultures, which were not significantly different from
each other within the fertilization treatment.
Fertilization did not increase the ratio of N2O emissions or sub-rooting zone NO3- concentrations to ANPP (Table 2). In most cases, fertilized polycultures had significantly lower ratios
than fertilized switchgrass. All systems had similar aboveground biomass N concentrations in
2011, while in 2012 restored prairie had the highest concentrations (Fig 2A and 2B). Fertilization increased aboveground N concentrations only in switchgrass and the native grasses, and
then only in 2011. Fertilization increased N removed in harvested biomass for switchgrass in
2011 and restored prairie in both years (Fig 2C and 2D). Switchgrass had the greatest N
removal in 2011, while in 2012 switchgrass and fertilized restored prairie had equivalent
removal rates.
Soil moisture and temperature
Average soil temperatures to 10 cm exhibited a crop × fertilizer interaction with significantly
higher temperatures in 2012 than 2011 (S1 and S2 Tables). In native grasses and restored prairie systems, unfertilized subplots were warmer. Soil WFPS exhibited a crop × year effect and
was consistently higher in unfertilized subplots (S1 and S2 Tables). Within each crop, WFPS in
2012 was lower than 2011. In 2011, WFPS in the native grasses was significantly lower than
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
Fig 2. Harvested biomass properties for each crop and fertilizer treatment in 2011 and 2012. Within each panel, samples sharing a letter are not
significantly different (P > 0.05). All values are arithmetic means ± standard error.
doi:10.1371/journal.pone.0151919.g002
other crops while in 2012 WFPS in the native grasses was lower than restored prairie but not
significantly different from switchgrass.
Discussion
We observed a cropping systems-level tradeoff between biomass production and loss of
environmentally harmful forms of nitrogen (N), with the native grasses and prairie species
mixtures having lower N2O emissions, potential NO3- leaching, and aboveground productivity.
N losses resulting from fertilization were greater and more consistent in switchgrass than in
the two polycultures, while productivity gains in response to fertilization were observed only in
the polycultures. Both mechanisms of N loss we considered in this study are heavily influenced
by precipitation and soil moisture; our measurements in the drought year of 2012 allowed us to
compare the interplay of soil moisture and labile N availability across the three cropping systems. Given that all three systems were managed identically following best practices for switchgrass production, our findings suggest that perennial grass-based polycultures handle fertilizerapplied N more robustly and efficiently than a switchgrass monoculture.
We hypothesize that many of our findings result from differences in how quickly and
completely the cropping systems we studied are able to immobilize applied N. This immobilization primarily entails incorporation of labile N into plant and microbial biomass [45]. Ideally, N fertilizer application should coincide with periods of heavy plant uptake, ensuring as
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
much N as possible is immobilized into plant tissues [8]. Predicting phenology in perennial
species is extremely challenging; in perennial bunch-forming grasses, like switchgrass, windows
for conducting field operations are further constrained by the need to avoid damage to plant
crowns. In this context, polycultures benefit greatly from seasonal complementarity, which has
been demonstrated to reduce labile N levels in soil [25]. Polycultures incorporate species with a
range of phenologies, so timing of plant N demand overlap to provide a broader time window
for efficient N uptake. In addition, both polycultures in our study contained significant components of cool-season grasses and/or forbs. These taxa have higher N demands and greater
early-season activity than a warm-season grass like switchgrass, and thus should have been
well-positioned to assimilate applied N.
Our N application rates were low, approximately half the rate recommended by University
of Wisconsin Extension for established switchgrass [8] and below the agronomically optimal
fertilization rate for a mixture of prairie species grown for biomass [15]. Despite this, the
amount of N we applied exceeded the amount removed as harvested biomass in all cases except
for the fertilized switchgrass in 2011. One guideline for N management in bioenergy crops is to
match application rates to the amount of N anticipated to be removed by biomass [46]. This
calculation can be complicated, as many perennial species, including switchgrass, are capable
of progressively relocating N from their aboveground biomass to their belowground tissues
over the period of senescence [47]. The N content of biomass can thus potentially vary interannually, depending on when in the senescence process the plants were harvested, as we observed
with broadly lower N contents in 2012. That said, we did not observe consistent, significant differences in biomass N concentrations across cropping systems. Rates of N removal were largely
due to differences in harvested biomass. It is curious that the polycultures had a greater excess
of N fertilization but lower levels of N loss. Most likely, much of the excess N was immobilized
into microbial biomass. Prairies in south-central Wisconsin support greater microbial biomass
than switchgrass fields [48], and in these soils biomass and necromass constitute a significant
component of the organic N pool [49]. It would be important to investigate the practical limits
of organic N accumulation in soils, as these would determine how these polycultures would
behave with long-term excessive N application.
Concentrations of NO3- at 50–80 cm responded strongly to cropping systems, N application, and yearly precipitation dynamics. These concentrations were dramatically higher in the
switchgrass system early in the season, decreasing sharply over time. Notably, while fertilization increased concentrations, the dynamic was still present in unfertilized switchgrass, indicating considerable free NO3- in the system early in the season. Given the limited root activity
occurring at these depths [34,35], these decreases likely represent loss of NO3- from the system,
rather than growing season uptake by plants. Concentrations were much lower in 2012, where
the lack of precipitation limited the percolation of water needed to transport NO3-. The contrast to the polycultures is stark and informative. In both systems, NO3- concentrations did not
increase in the early season, did not increase with fertilization, and were largely the same in the
normal and drought years. These observations strongly suggest that, even following fertilization in a year with normal precipitation, soil NO3- levels in the polycultural systems were low
enough to avoid significant leaching. This demonstrated the capacity of these polycultural systems to rapidly and efficiently immobilize fertilizer N.
Patterns of N2O emissions similarly reflected differences in N immobilization efficiency
across cropping systems, fertilization managements, and years. Soils can produce N2O through
both the processes of nitrification and denitrification, but in soils with adequate moisture, such
as at our study site, flux dynamics are dominated by denitrification [50]. Denitrification uses
free NO3- as an alternative electron acceptor under low oxygen conditions. Typically, large
N2O fluxes are observed when precipitation events, which reduce oxygen availability by
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
restricting gas movement in the soil, coincide with high concentrations of NO3-, which is usually the limiting substrate for the reaction [27]. The lower N2O emissions observed in the fertilized polycultures in the normal precipitation year of 2011 illustrate how effectively these
systems were able to immobilize N between the time it was applied and the next major precipitation event. The lack of spring precipitation in 2012, by contrast, provided greater time for N
immobilization. This was sufficient to completely erase the fertilizer effect in the polycultures,
but the effect was still clearly visible in the switchgrass, suggesting that the systems differed
both in the speed and the thoroughness of their N immobilization. It should be noted that in
2011 switchgrass had slightly higher soil moisture, potentially accounting for some of the
increase in emissions, but soil moistures were comparable across systems in 2012 while emission differences remained.
In light of the N immobilization dynamics we observed, the productivity responses to N fertilization suggest the polycultures were mildly N-limited, while the switchgrass was not.
Switchgrass responds unevenly to N fertilization [51], which can even decrease switchgrass
productivity under high soil N conditions [52]. Fertilization may indirectly inhibit switchgrass
growth by stimulating forb and cool-season grass weeds, which can be detrimental to switchgrass productivity [53] and stand establishment [13,14]. The polycultures, by contrast, deliberately included highly productive forbs and cool-season grasses, whose stimulation by N
addition contributed to the system's productivity. It needs to be noted, however, that fertilized
and unfertilized switchgrass were at least as productive as the polycultures, as has been previously reported [54]. The polycultures juxtaposed low N losses with productivity gains in
response to fertilization, suggesting these systems were N limited. It is possible that the microbial biomass in these systems competed with the plants for nitrogen [55], an interaction that
may complicate management of these systems.
Our findings hold significant implications for the selection and management of perennial
bioenergy cropping systems. Selecting a bioenergy cropping system may entail balancing biomass production needs with N pollution risks, although productivity gains through optimization of polyculture species assemblages may be possible. Our results show, with respect to
nitrogen processing, polycultural biomass production systems can be resilient in the face of
annual weather fluctuations which indicates the environmental and management benefits of
these systems should not be overlooked.
Supporting Information
S1 Fig. High-frequency soil and climate measurements collected from a single switchgrass
plot in the Bioenergy Cropping Systems Experiment at Arlington Agricultural Research
Station.
(PDF)
S2 Fig. Biofuels Cropping System Experiment (BCSE) plot dimensions and sampling
design.
(PDF)
S3 Fig. Growing season soil nitrate concentrations at 50 to 80 cm.
(PDF)
S1 Table. Mean growing season soil temperature and water filled pore space (WFPS) to 10
cm by cropping system, year, and fertilization.
(PDF)
PLOS ONE | DOI:10.1371/journal.pone.0151919 March 18, 2016
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Fertilization Effects on Productivity and Nitrogen Loss in Perennial Bioenergy Cropping Systems
S2 Table. Variance partitioning of effects of year, cropping system, and fertilization on
mean growing season soil temperature and water filled pore space (WFPS) to 10 cm.
(PDF)
Acknowledgments
We would like to thank T.D. Burhop, M.J. Cruse, A. David, T. Davis, S.M. Greenler, J.D.
Lechelt, N. Lee, C. Liu, and A.C. Perillo for their assistance in field sampling, and G.R. Sanford
for agronomic management. Comments from K. Stahlheber, S.M. Marion, L.C. Smith, A.
Cates, and multiple anonymous reviewers were helpful improving this manuscript.
Author Contributions
Conceived and designed the experiments: BELD CJK RDJ. Performed the experiments: BELD.
Analyzed the data: BELD DSD LGO. Contributed reagents/materials/analysis tools: LGO CJK
RDJ. Wrote the paper: BELD DSD LGO CJK RDJ.
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